Applying custom function to a column of lists in pandas, how to handle exceptions?

I have a data frame of 15000 record which has text column (column name = clean) as a list, please refer below

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I need to find the minimum value in each row and add as a new column called min

def find_min(x):
    x = min(x)
    return(x)

I tried to pass the above function

df1['min'] = df1['clean'].map(find_min)

Getting below error

ValueError: min() arg is an empty sequence

It seems there is an empty list, how to address this as I am having 15000 records Please advise

Answer

Since we have a list of columns, let us try handling errors in your function using try/except (EAFP pattern):

def find_min(x):
    try: 
        return min(x)
    except ValueError:
        return np.nan

df1['min'] = df1['clean'].map(find_min)

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Another way is to skip the function and define this inline:

df1['min'] = df1['clean'].map(lambda x: min(x) if len(x) else np.nan)

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You can also do this using a list comprehension, which is quite fast:

df1['min'] = [find_min(x) for x in df1['clean']]

or,

df1['min'] = [min(x) if len(x) else np.nan for x in df1['clean']]